Datasets:
File size: 1,465 Bytes
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dataset_info:
features:
- name: image
dtype: image
- name: mask
dtype: image
- name: split
dtype: string
splits:
- name: train
num_bytes: 34450965
num_examples: 3345
download_size: 249337909
dataset_size: 34450965
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: cc0-1.0
task_categories:
- image-segmentation
size_categories:
- 1K<n<10K
---
# Strawberry Runner Segmentation
A dataset for semantic segmentation of strawberry runners. The dataset contains 3,345 images with pixel-level mask annotations.
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
The original train/test/val split has been preserved in the `split` column.
## Citation
```bibtex
@article{zhou2025deep,
title={Deep learning for strawberry runner detection integrating ground and aerial imaging},
author={Zhou, Xue and Wang, Xu and Ji, Liyike and Daggubati, Santhi and Shen, Kai and Whitaker, Vance M.},
journal={Smart Agricultural Technology},
volume={12},
pages={101290},
year={2025},
publisher={Elsevier}
}
```
Zhou, Xue; Wang, Xu; Whitaker, Vance et al. (2025). Ground and aerial imagery dataset for strawberry breeding trials: Training deep learning models for runner detection and segmentation [Dataset]. Dryad. https://doi.org/10.5061/dryad.bzkh189nw
*This dataset was reformatted from its original format to match HuggingFace standards.* |